Elusiveness Of BI TEI

by Boris Evelson.

Why is BI TEI (Total Economic Impact) so elusive? Recently I reached out to all major BI software vendors and asked them to provide a customer reference who's willing to stand up and confirm a hard $ return on investment from BI implementation. Guess how many takers I got? None. Yes many are willing to point to expected savings and benefits, but no one's gone back and calculated the actual results. Why? It is definitely very complex. For example:

Costs

  • Make sure you account for both direct and indirect costs.
  • Direct costs are the obvious expenses and capital expenditures associated with BI software, hardware and consulting services. A good rule of thumb is to expect to pay $5-$7 dollars for system integration and management consulting for every $1 you pay for software. And don't forget to include the costs of training and on-going support.
  • Indirect costs are for software/hardware/services for non-BI specific components which are nevertheless necessary to achieve a successful BI implementation: data quality, master data management, metadata implementation, portals, collaboration, knowledge management and many others. The indirect costs are not as easy to quantify. For example, do you attribute the cost of implementing a data quality solution to the BI initiative? Most likely your data quality problems exist in your sources, so one might think it should be a separate effort. However, very often you identify data quality problems when you build your first BI solution, so there may be a tendency to bundle in these costs into the BI project. As a result, these indirect costs are notoriously difficult to identify and negotiate (with other stakeholders), but nevertheless they are a major component of the total cost.

Benefits

  • Cost savings are typically very difficult to realize. Since it's pretty impossible to become 100% more efficient even with the best BI tool, one can typically realize only 20%-30% efficiency gain with a better BI tool, better BI architecture. Since you can't lay off 20% of an employee, the savings are not that clear.
  • Increased and/or new revenues. Additional revenues can come from increased effectiveness (higher response rates on a marketing campaign, for example) or new revenues from newly discovered opportunities (a more effective customer segmentation, for example, may uncover a new, previously unaddressed customer segment). I know of no scientific method, however, to predict the outcome ahead of time and therefore get a sense of new/additional revenue streams before the project. One can only do that by comparing new, BI enabled, initiatives to the old ones.
  • Risk avoidance. Better information, insight and improved decision making always translate to potentially lower risks. Again, it's very hard to predict — one would need to compare typical loss due to operational (or credit or market) events before and after implementing a BI environment.
  • Non financial benefits are hard to figure into the ROI calculation, but they are typically major drivers behind BI projects. These may include increased employee and customer satisfaction, better competitive awareness of the market, and many others.

So, I am throwing a challenge out there. Show me a bottom line, proven, documented $ BI TEI and we'll publish it!